Sisense Leverages Machine Learning to Alert Business Users to Data Anomalies

Sisense has launched Sisense Pulse, a new alerting system that provides proactive notifications about a user’s most important business events, in real time when changes occur. 

Sisense Pulse leverages machine learning technology to analyze and learn data patterns to detect and proactively tell users about anomalies, to help make it easier for users to track the KPIs that matter most to their business.

With Sisense Pulse, business users are given the power to automate KPI tracking in a systematic way, removing the need to review and monitor multiple dashboards and run manual analyses to identify outliers. This feature enables business users to be more in tune with their key KPIs, and arms them with the insights they need to immediately take action when an anomaly occurs. 

According to Amir Orad, CEO of Sisense, businesses are facing more pressure to quickly analyze and interpret complex data, and in order to stay competitive, they need BI and analytics tools that are proactive, intuitive and that enable them to take action in real time.  To that end, Sisense Pulse is able to detect anomalies without users having to define outliers and variations at the outset. By leveraging machine learning technology, Sisense Pulse learns key metrics based on historical data to determine what is normal and what an acceptable variation is at any given moment. If that metric varies significantly from what the system has learned it should be, it sends a smart alert in real time, inspiring the user to take action. 

Sisense also enables users to create a fully automated workflow using Zapier or another generalized webhook framework. The insights generated by Pulse and its machine learning capability are actionable throughout the organization, triggering automatic actions with other internal systems.

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